Ji, Jie, Li, Gen, Fu, Jingjing, Afghah, Fatemeh, Guo, Linke, Yuan, Xiaoyong, and Ma, Xiaolong. A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training. Retrieved from https://par.nsf.gov/biblio/10588432.

Ji, Jie, Li, Gen, Fu, Jingjing, Afghah, Fatemeh, Guo, Linke, Yuan, Xiaoyong, & Ma, Xiaolong. A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training. Retrieved from https://par.nsf.gov/biblio/10588432.

Ji, Jie, Li, Gen, Fu, Jingjing, Afghah, Fatemeh, Guo, Linke, Yuan, Xiaoyong, and Ma, Xiaolong. "A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training". Country unknown/Code not available: 38th Conference on Neural Information Processing Systems (NeurIPS 2024).. https://par.nsf.gov/biblio/10588432.

@article{osti_10588432,
place = {Country unknown/Code not available}, title = {A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training}, url = {https://par.nsf.gov/biblio/10588432}, abstractNote = {}, journal = {}, publisher = {38th Conference on Neural Information Processing Systems (NeurIPS 2024).}, author = {Ji, Jie and Li, Gen and Fu, Jingjing and Afghah, Fatemeh and Guo, Linke and Yuan, Xiaoyong and Ma, Xiaolong}, }